title: Sensitivity of two dispersion models (AERMOD and ISCST3) to input parameters for a rural ground-level area source.
abstract: As of December 2006, the American Meteorological Society/U.S. Environmental Protection Agency (EPA) Regulatory Model with Plume Rise Model Enhancements (AERMOD-PRIME; hereafter AERMOD) replaced the Industrial Source Complex Short Term Version 3 (ISCST3) as the EPA-preferred regulatory model. The change from ISCST3 to AERMOD will affect Prevention of Significant Deterioration (PSD) increment consumption as well as permit compliance in states where regulatory agencies limit property line concentrations using modeling analysis. Because of differences in model formulation and the treatment of terrain features, one cannot predict a priori whether ISCST3 or AERMOD will predict higher or lower pollutant concentrations downwind of a source. The objectives of this paper were to determine the sensitivity of AERMOD to various inputs and compare the highest downwind concentrations from a ground-level area source (GLAS) predicted by AERMOD to those predicted by ISCST3. Concentrations predicted using ISCST3 were sensitive to changes in wind speed, temperature, solar radiation (as it affects stability class), and mixing heights below 160 m. Surface roughness also affected downwind concentrations predicted by ISCST3. AERMOD was sensitive to changes in albedo, surface roughness, wind speed, temperature, and cloud cover. Bowen ratio did not affect the results from AERMOD. These results demonstrate AERMOD's sensitivity to small changes in wind speed and surface roughness. When AERMOD is used to determine property line concentrations, small changes in these variables may affect the distance within which concentration limits are exceeded by several hundred meters.
authors.affiliation: Department of Biological and Agricultural Engineering, Texas A&M University, College Station, TX 77843-2117, USA. faulkner@tamu.edu
authors.forename: William B
authors.initials: WB
authors.lastname: Faulkner
authors.forename: Bryan W
authors.initials: BW
authors.lastname: Shaw
authors.forename: Tom
authors.initials: T
authors.lastname: Grosch
mesh_terms: D000397:Air Pollution / Q000706:statistics & numerical data*; D000465:Algorithms; D015233:Models, Statistical; D012993:Solar Energy; D013696:Temperature; D014887:Weather; D014919:Wind